Trajectory planning has long been a critical problem in robotics. As trajectory planning affects the quality of robots’ motion to a great extent, people have long been investigating this problem for various kinds of robots [1]}. Pioneered by Mellinger et al. [2]}, minimum-snap has been dominantly used in quadrotors trajectory planning. Minimum-snap takes the snap of the whole trajectory as cost and generates the planning problem in the form of a quadratic program (QP). Meanwhile, various equality or inequality constraints with different requirements on the trajectory can be added to the QP, making it convenient for addressing more complex tasks.
